|
|
@@ -0,0 +1,405 @@
|
|
|
+/**
|
|
|
+ * Licensed to the Apache Software Foundation (ASF) under one
|
|
|
+ * or more contributor license agreements. See the NOTICE file
|
|
|
+ * distributed with this work for additional information
|
|
|
+ * regarding copyright ownership. The ASF licenses this file
|
|
|
+ * to you under the Apache License, Version 2.0 (the
|
|
|
+ * "License"); you may not use this file except in compliance
|
|
|
+ * with the License. You may obtain a copy of the License at
|
|
|
+ *
|
|
|
+ * http://www.apache.org/licenses/LICENSE-2.0
|
|
|
+ *
|
|
|
+ * Unless required by applicable law or agreed to in writing, software
|
|
|
+ * distributed under the License is distributed on an "AS IS" BASIS,
|
|
|
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
|
+ * See the License for the specific language governing permissions and
|
|
|
+ * limitations under the License.
|
|
|
+ */
|
|
|
+package org.apache.hadoop.mapred;
|
|
|
+
|
|
|
+import java.io.ByteArrayOutputStream;
|
|
|
+import java.io.DataOutputStream;
|
|
|
+import java.io.IOException;
|
|
|
+import java.io.OutputStream;
|
|
|
+import java.io.OutputStreamWriter;
|
|
|
+import java.io.Writer;
|
|
|
+
|
|
|
+import org.apache.hadoop.conf.Configuration;
|
|
|
+
|
|
|
+import org.apache.hadoop.fs.FSDataInputStream;
|
|
|
+import org.apache.hadoop.fs.FSDataOutputStream;
|
|
|
+import org.apache.hadoop.fs.FileSystem;
|
|
|
+import org.apache.hadoop.fs.FileUtil;
|
|
|
+import org.apache.hadoop.fs.LocalFileSystem;
|
|
|
+import org.apache.hadoop.fs.Path;
|
|
|
+
|
|
|
+import org.apache.hadoop.hdfs.MiniDFSCluster;
|
|
|
+
|
|
|
+import org.apache.hadoop.io.DataOutputBuffer;
|
|
|
+import org.apache.hadoop.io.LongWritable;
|
|
|
+import org.apache.hadoop.io.Text;
|
|
|
+import org.apache.hadoop.io.WritableUtils;
|
|
|
+
|
|
|
+import org.apache.hadoop.io.serializer.SerializationFactory;
|
|
|
+import org.apache.hadoop.io.serializer.Serializer;
|
|
|
+
|
|
|
+import org.apache.hadoop.mapred.Task.TaskReporter;
|
|
|
+
|
|
|
+import junit.framework.TestCase;
|
|
|
+
|
|
|
+@SuppressWarnings(value={"unchecked", "deprecation"})
|
|
|
+/**
|
|
|
+ * This test tests the support for a merge operation in Hadoop. The input files
|
|
|
+ * are already sorted on the key. This test implements an external
|
|
|
+ * MapOutputCollector implementation that just copies the records to different
|
|
|
+ * partitions while maintaining the sort order in each partition. The Hadoop
|
|
|
+ * framework's merge on the reduce side will merge the partitions created to
|
|
|
+ * generate the final output which is sorted on the key.
|
|
|
+ */
|
|
|
+public class TestMerge extends TestCase {
|
|
|
+ private static final int NUM_HADOOP_DATA_NODES = 2;
|
|
|
+ // Number of input files is same as the number of mappers.
|
|
|
+ private static final int NUM_MAPPERS = 10;
|
|
|
+ // Number of reducers.
|
|
|
+ private static final int NUM_REDUCERS = 4;
|
|
|
+ // Number of lines per input file.
|
|
|
+ private static final int NUM_LINES = 1000;
|
|
|
+ // Where MR job's input will reside.
|
|
|
+ private static final Path INPUT_DIR = new Path("/testplugin/input");
|
|
|
+ // Where output goes.
|
|
|
+ private static final Path OUTPUT = new Path("/testplugin/output");
|
|
|
+
|
|
|
+ public void testMerge() throws Exception {
|
|
|
+ MiniDFSCluster dfsCluster = null;
|
|
|
+ MiniMRClientCluster mrCluster = null;
|
|
|
+ FileSystem fileSystem = null;
|
|
|
+ try {
|
|
|
+ Configuration conf = new Configuration();
|
|
|
+ // Start the mini-MR and mini-DFS clusters
|
|
|
+ dfsCluster = new MiniDFSCluster(conf, NUM_HADOOP_DATA_NODES, true, null);
|
|
|
+ fileSystem = dfsCluster.getFileSystem();
|
|
|
+ mrCluster = MiniMRClientClusterFactory.create(this.getClass(),
|
|
|
+ NUM_HADOOP_DATA_NODES, conf);
|
|
|
+ // Generate input.
|
|
|
+ createInput(fileSystem);
|
|
|
+ // Run the test.
|
|
|
+ runMergeTest(new JobConf(mrCluster.getConfig()), fileSystem);
|
|
|
+ } finally {
|
|
|
+ if (dfsCluster != null) {
|
|
|
+ dfsCluster.shutdown();
|
|
|
+ }
|
|
|
+ if (mrCluster != null) {
|
|
|
+ mrCluster.stop();
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private void createInput(FileSystem fs) throws Exception {
|
|
|
+ fs.delete(INPUT_DIR, true);
|
|
|
+ for (int i = 0; i < NUM_MAPPERS; i++) {
|
|
|
+ OutputStream os = fs.create(new Path(INPUT_DIR, "input_" + i + ".txt"));
|
|
|
+ Writer writer = new OutputStreamWriter(os);
|
|
|
+ for (int j = 0; j < NUM_LINES; j++) {
|
|
|
+ // Create sorted key, value pairs.
|
|
|
+ int k = j + 1;
|
|
|
+ String formattedNumber = String.format("%09d", k);
|
|
|
+ writer.write(formattedNumber + " " + formattedNumber + "\n");
|
|
|
+ }
|
|
|
+ writer.close();
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private void runMergeTest(JobConf job, FileSystem fileSystem)
|
|
|
+ throws Exception {
|
|
|
+ // Delete any existing output.
|
|
|
+ fileSystem.delete(OUTPUT, true);
|
|
|
+ job.setJobName("MergeTest");
|
|
|
+ JobClient client = new JobClient(job);
|
|
|
+ RunningJob submittedJob = null;
|
|
|
+ FileInputFormat.setInputPaths(job, INPUT_DIR);
|
|
|
+ FileOutputFormat.setOutputPath(job, OUTPUT);
|
|
|
+ job.set("mapreduce.output.textoutputformat.separator", " ");
|
|
|
+ job.setInputFormat(TextInputFormat.class);
|
|
|
+ job.setMapOutputKeyClass(Text.class);
|
|
|
+ job.setMapOutputValueClass(Text.class);
|
|
|
+ job.setOutputKeyClass(Text.class);
|
|
|
+ job.setOutputValueClass(Text.class);
|
|
|
+ job.setMapperClass(MyMapper.class);
|
|
|
+ job.setPartitionerClass(MyPartitioner.class);
|
|
|
+ job.setOutputFormat(TextOutputFormat.class);
|
|
|
+ job.setNumReduceTasks(NUM_REDUCERS);
|
|
|
+ job.set(JobContext.MAP_OUTPUT_COLLECTOR_CLASS_ATTR,
|
|
|
+ MapOutputCopier.class.getName());
|
|
|
+ try {
|
|
|
+ submittedJob = client.submitJob(job);
|
|
|
+ try {
|
|
|
+ if (! client.monitorAndPrintJob(job, submittedJob)) {
|
|
|
+ throw new IOException("Job failed!");
|
|
|
+ }
|
|
|
+ } catch(InterruptedException ie) {
|
|
|
+ Thread.currentThread().interrupt();
|
|
|
+ }
|
|
|
+ } catch(IOException ioe) {
|
|
|
+ System.err.println("Job failed with: " + ioe);
|
|
|
+ } finally {
|
|
|
+ verifyOutput(submittedJob, fileSystem);
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ private void verifyOutput(RunningJob submittedJob, FileSystem fileSystem)
|
|
|
+ throws Exception {
|
|
|
+ FSDataInputStream dis = null;
|
|
|
+ long numValidRecords = 0;
|
|
|
+ long numInvalidRecords = 0;
|
|
|
+ long numMappersLaunched = NUM_MAPPERS;
|
|
|
+ String prevKeyValue = "000000000";
|
|
|
+ Path[] fileList =
|
|
|
+ FileUtil.stat2Paths(fileSystem.listStatus(OUTPUT,
|
|
|
+ new Utils.OutputFileUtils.OutputFilesFilter()));
|
|
|
+ for (Path outFile : fileList) {
|
|
|
+ try {
|
|
|
+ dis = fileSystem.open(outFile);
|
|
|
+ String record;
|
|
|
+ while((record = dis.readLine()) != null) {
|
|
|
+ // Split the line into key and value.
|
|
|
+ int blankPos = record.indexOf(" ");
|
|
|
+ String keyString = record.substring(0, blankPos);
|
|
|
+ String valueString = record.substring(blankPos+1);
|
|
|
+ // Check for sorted output and correctness of record.
|
|
|
+ if (keyString.compareTo(prevKeyValue) >= 0
|
|
|
+ && keyString.equals(valueString)) {
|
|
|
+ prevKeyValue = keyString;
|
|
|
+ numValidRecords++;
|
|
|
+ } else {
|
|
|
+ numInvalidRecords++;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ } finally {
|
|
|
+ if (dis != null) {
|
|
|
+ dis.close();
|
|
|
+ dis = null;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ // Make sure we got all input records in the output in sorted order.
|
|
|
+ assertEquals((long)(NUM_MAPPERS*NUM_LINES), numValidRecords);
|
|
|
+ // Make sure there is no extraneous invalid record.
|
|
|
+ assertEquals(0, numInvalidRecords);
|
|
|
+ }
|
|
|
+
|
|
|
+ /**
|
|
|
+ * A mapper implementation that assumes that key text contains valid integers
|
|
|
+ * in displayable form.
|
|
|
+ */
|
|
|
+ public static class MyMapper extends MapReduceBase
|
|
|
+ implements Mapper<LongWritable, Text, Text, Text> {
|
|
|
+ private Text keyText;
|
|
|
+ private Text valueText;
|
|
|
+
|
|
|
+ public MyMapper() {
|
|
|
+ keyText = new Text();
|
|
|
+ valueText = new Text();
|
|
|
+ }
|
|
|
+
|
|
|
+ @Override
|
|
|
+ public void map(LongWritable key, Text value,
|
|
|
+ OutputCollector<Text, Text> output,
|
|
|
+ Reporter reporter) throws IOException {
|
|
|
+ String record = value.toString();
|
|
|
+ int blankPos = record.indexOf(" ");
|
|
|
+ keyText.set(record.substring(0, blankPos));
|
|
|
+ valueText.set(record.substring(blankPos+1));
|
|
|
+ output.collect(keyText, valueText);
|
|
|
+ }
|
|
|
+
|
|
|
+ public void close() throws IOException {
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ /**
|
|
|
+ * Partitioner implementation to make sure that output is in total sorted
|
|
|
+ * order. We basically route key ranges to different reducers such that
|
|
|
+ * key values monotonically increase with the partition number. For example,
|
|
|
+ * in this test, the keys are numbers from 1 to 1000 in the form "000000001"
|
|
|
+ * to "000001000" in each input file. The keys "000000001" to "000000250" are
|
|
|
+ * routed to partition 0, "000000251" to "000000500" are routed to partition 1
|
|
|
+ * and so on since we have 4 reducers.
|
|
|
+ */
|
|
|
+ static class MyPartitioner implements Partitioner<Text, Text> {
|
|
|
+ public MyPartitioner() {
|
|
|
+ }
|
|
|
+
|
|
|
+ public void configure(JobConf job) {
|
|
|
+ }
|
|
|
+
|
|
|
+ public int getPartition(Text key, Text value, int numPartitions) {
|
|
|
+ int keyValue = 0;
|
|
|
+ try {
|
|
|
+ keyValue = Integer.parseInt(key.toString());
|
|
|
+ } catch(NumberFormatException nfe) {
|
|
|
+ keyValue = 0;
|
|
|
+ }
|
|
|
+ int partitionNumber = (numPartitions*(Math.max(0, keyValue-1)))/NUM_LINES;
|
|
|
+ return partitionNumber;
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ /**
|
|
|
+ * Implementation of map output copier(that avoids sorting) on the map side.
|
|
|
+ * It maintains keys in the input order within each partition created for
|
|
|
+ * reducers.
|
|
|
+ */
|
|
|
+ static class MapOutputCopier<K, V>
|
|
|
+ implements MapOutputCollector<K, V> {
|
|
|
+ private static final int BUF_SIZE = 128*1024;
|
|
|
+ private MapTask mapTask;
|
|
|
+ private JobConf jobConf;
|
|
|
+ private TaskReporter reporter;
|
|
|
+ private int numberOfPartitions;
|
|
|
+ private Class<K> keyClass;
|
|
|
+ private Class<V> valueClass;
|
|
|
+ private KeyValueWriter<K, V> recordWriters[];
|
|
|
+ private ByteArrayOutputStream outStreams[];
|
|
|
+
|
|
|
+ public MapOutputCopier() {
|
|
|
+ }
|
|
|
+
|
|
|
+ @SuppressWarnings("unchecked")
|
|
|
+ public void init(MapOutputCollector.Context context)
|
|
|
+ throws IOException, ClassNotFoundException {
|
|
|
+ this.mapTask = context.getMapTask();
|
|
|
+ this.jobConf = context.getJobConf();
|
|
|
+ this.reporter = context.getReporter();
|
|
|
+ numberOfPartitions = jobConf.getNumReduceTasks();
|
|
|
+ keyClass = (Class<K>)jobConf.getMapOutputKeyClass();
|
|
|
+ valueClass = (Class<V>)jobConf.getMapOutputValueClass();
|
|
|
+ recordWriters = new KeyValueWriter[numberOfPartitions];
|
|
|
+ outStreams = new ByteArrayOutputStream[numberOfPartitions];
|
|
|
+
|
|
|
+ // Create output streams for partitions.
|
|
|
+ for (int i = 0; i < numberOfPartitions; i++) {
|
|
|
+ outStreams[i] = new ByteArrayOutputStream();
|
|
|
+ recordWriters[i] = new KeyValueWriter<K, V>(jobConf, outStreams[i],
|
|
|
+ keyClass, valueClass);
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ public synchronized void collect(K key, V value, int partitionNumber
|
|
|
+ ) throws IOException, InterruptedException {
|
|
|
+ if (partitionNumber >= 0 && partitionNumber < numberOfPartitions) {
|
|
|
+ recordWriters[partitionNumber].write(key, value);
|
|
|
+ } else {
|
|
|
+ throw new IOException("Invalid partition number: " + partitionNumber);
|
|
|
+ }
|
|
|
+ reporter.progress();
|
|
|
+ }
|
|
|
+
|
|
|
+ public void close() throws IOException, InterruptedException {
|
|
|
+ long totalSize = 0;
|
|
|
+ for (int i = 0; i < numberOfPartitions; i++) {
|
|
|
+ recordWriters[i].close();
|
|
|
+ outStreams[i].close();
|
|
|
+ totalSize += outStreams[i].size();
|
|
|
+ }
|
|
|
+ MapOutputFile mapOutputFile = mapTask.getMapOutputFile();
|
|
|
+ Path finalOutput = mapOutputFile.getOutputFileForWrite(totalSize);
|
|
|
+ Path indexPath = mapOutputFile.getOutputIndexFileForWrite(
|
|
|
+ numberOfPartitions*mapTask.MAP_OUTPUT_INDEX_RECORD_LENGTH);
|
|
|
+ // Copy partitions to final map output.
|
|
|
+ copyPartitions(finalOutput, indexPath);
|
|
|
+ }
|
|
|
+
|
|
|
+ public void flush() throws IOException, InterruptedException,
|
|
|
+ ClassNotFoundException {
|
|
|
+ }
|
|
|
+
|
|
|
+ private void copyPartitions(Path mapOutputPath, Path indexPath)
|
|
|
+ throws IOException {
|
|
|
+ FileSystem localFs = FileSystem.getLocal(jobConf);
|
|
|
+ FileSystem rfs = ((LocalFileSystem)localFs).getRaw();
|
|
|
+ FSDataOutputStream rawOutput = rfs.create(mapOutputPath, true, BUF_SIZE);
|
|
|
+ SpillRecord spillRecord = new SpillRecord(numberOfPartitions);
|
|
|
+ IndexRecord indexRecord = new IndexRecord();
|
|
|
+ for (int i = 0; i < numberOfPartitions; i++) {
|
|
|
+ indexRecord.startOffset = rawOutput.getPos();
|
|
|
+ byte buffer[] = outStreams[i].toByteArray();
|
|
|
+ IFileOutputStream checksumOutput = new IFileOutputStream(rawOutput);
|
|
|
+ checksumOutput.write(buffer);
|
|
|
+ // Write checksum.
|
|
|
+ checksumOutput.finish();
|
|
|
+ // Write index record
|
|
|
+ indexRecord.rawLength = (long)buffer.length;
|
|
|
+ indexRecord.partLength = rawOutput.getPos() - indexRecord.startOffset;
|
|
|
+ spillRecord.putIndex(indexRecord, i);
|
|
|
+ reporter.progress();
|
|
|
+ }
|
|
|
+ rawOutput.close();
|
|
|
+ spillRecord.writeToFile(indexPath, jobConf);
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ static class KeyValueWriter<K, V> {
|
|
|
+ private Class<K> keyClass;
|
|
|
+ private Class<V> valueClass;
|
|
|
+ private DataOutputBuffer dataBuffer;
|
|
|
+ private Serializer<K> keySerializer;
|
|
|
+ private Serializer<V> valueSerializer;
|
|
|
+ private DataOutputStream outputStream;
|
|
|
+
|
|
|
+ public KeyValueWriter(Configuration conf, OutputStream output,
|
|
|
+ Class<K> kyClass, Class<V> valClass
|
|
|
+ ) throws IOException {
|
|
|
+ keyClass = kyClass;
|
|
|
+ valueClass = valClass;
|
|
|
+ dataBuffer = new DataOutputBuffer();
|
|
|
+ SerializationFactory serializationFactory
|
|
|
+ = new SerializationFactory(conf);
|
|
|
+ keySerializer
|
|
|
+ = (Serializer<K>)serializationFactory.getSerializer(keyClass);
|
|
|
+ keySerializer.open(dataBuffer);
|
|
|
+ valueSerializer
|
|
|
+ = (Serializer<V>)serializationFactory.getSerializer(valueClass);
|
|
|
+ valueSerializer.open(dataBuffer);
|
|
|
+ outputStream = new DataOutputStream(output);
|
|
|
+ }
|
|
|
+
|
|
|
+ public void write(K key, V value) throws IOException {
|
|
|
+ if (key.getClass() != keyClass) {
|
|
|
+ throw new IOException("wrong key class: "+ key.getClass()
|
|
|
+ +" is not "+ keyClass);
|
|
|
+ }
|
|
|
+ if (value.getClass() != valueClass) {
|
|
|
+ throw new IOException("wrong value class: "+ value.getClass()
|
|
|
+ +" is not "+ valueClass);
|
|
|
+ }
|
|
|
+ // Append the 'key'
|
|
|
+ keySerializer.serialize(key);
|
|
|
+ int keyLength = dataBuffer.getLength();
|
|
|
+ if (keyLength < 0) {
|
|
|
+ throw new IOException("Negative key-length not allowed: " + keyLength +
|
|
|
+ " for " + key);
|
|
|
+ }
|
|
|
+ // Append the 'value'
|
|
|
+ valueSerializer.serialize(value);
|
|
|
+ int valueLength = dataBuffer.getLength() - keyLength;
|
|
|
+ if (valueLength < 0) {
|
|
|
+ throw new IOException("Negative value-length not allowed: " +
|
|
|
+ valueLength + " for " + value);
|
|
|
+ }
|
|
|
+ // Write the record out
|
|
|
+ WritableUtils.writeVInt(outputStream, keyLength);
|
|
|
+ WritableUtils.writeVInt(outputStream, valueLength);
|
|
|
+ outputStream.write(dataBuffer.getData(), 0, dataBuffer.getLength());
|
|
|
+ // Reset
|
|
|
+ dataBuffer.reset();
|
|
|
+ }
|
|
|
+
|
|
|
+ public void close() throws IOException {
|
|
|
+ keySerializer.close();
|
|
|
+ valueSerializer.close();
|
|
|
+ WritableUtils.writeVInt(outputStream, IFile.EOF_MARKER);
|
|
|
+ WritableUtils.writeVInt(outputStream, IFile.EOF_MARKER);
|
|
|
+ outputStream.close();
|
|
|
+ }
|
|
|
+ }
|
|
|
+}
|
Alejandro Abdelnur